Wireless communication has moved through five complete technology generations in roughly four decades, and each transition has reshaped how societies exchange information, run businesses, and design cities. This paper is the first instalment of a two-part review and concentrates on the historical arc of that journey, tracing the defining traits, benefits, and shortcomings of 1G through 5G before turning to the architectural groundwork on which sixth-generation (6G) networks are being built. Particular attention is paid to how sixth-generation systems are expected to fold artificial intelligence (AI) directly into the network fabric through a Digital Twin (DT) framework, rather than bolting it on as an external add-on. We also examine the energy-optimisation strategies that will decide whether 6G's ambitious performance targets can be met without a runaway rise in power consumption. To make the generational transition easier to visualise, we include a comparative summary table together with two illustrative charts depicting the approximate growth in peak data rate and the corresponding fall in latency across generations. The discussion closes by outlining the DT communication mechanism and the twin-loop management structure that is likely to underpin autonomous 6G operation, setting the stage for the companion paper, which examines specific AI techniques and air-interface optimisation methods in detail.

Keywords - 6G networks, mobile generations, wireless evolution, Digital Twin, network architecture, energy efficiency, artificial intelligence.

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1. Chowdhury MZ, Shahjalal M, Ahmed S, Jang YM. 6G wireless communication systems: Applications, requirements, technologies, challenges, and research directions. IEEE Open Journal of the Communications Society. 2020 Jul 20;1:957-75.
2. Saad W, Bennis M, Chen M. A vision of 6G wireless systems: Applications, trends, technologies, and open research problems. IEEE network. 2019 Oct 15;34(3):134-42.
3. Tataria H, Shafi M, Molisch AF, Dohler M, Sjöland H, Tufvesson F. 6G wireless systems: Vision, requirements, challenges, insights, and opportunities. Proceedings of the IEEE. 2021 Mar 30;109(7):1166-99.
4. Recommendation IT. Framework and overall objectives of the future development of IMT for 2030 and beyond. International Telecommunication Union (ITU) Recommendation (ITU- R). 2023 Jun.
5. Yuan Y, Zhao Y, Zong B, Parolari S. Potential key technologies for 6G mobile communications. Science China Information Sciences. 2020 Aug;63(8):183301.
6. Tao F, Zhang M. Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing. IEEE access. 2017 Sep 25;5:20418-27.
7. Tao F, Qi Q, Wang L, Nee AY. Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparison. Engineering. 2019 Aug 1;5(4):653-61.
8. Tao F, Zhang H, Liu A, Nee AY. Digital twin in industry: State-of-the-art. IEEE Transactions on industrial informatics. 2018 Oct 1;15(4):2405-15.
9. Rappaport TS, Xing Y, Kanhere O, Ju S, Madanayake A, Mandal S, Alkhateeb A, Trichopoulos GC. Wireless communications and applications above 100 GHz: Opportunities and challenges for 6G and beyond. IEEE access. 2019 Jun 6;7:78729-57.
10. Ma L, Grant M, Lin H, Sköld J, Liu R, Shao J. From Vision to Design Targets: Technical Performance Requirements for IMT-2030. IEEE Communications Magazine. 2026 Jun 3;64(6):6-9.
11. Cui Q, You X, Wei N, Nan G, Zhang X, Zhang J, Lyu X, Ai M, Tao X, Feng Z, Zhang P. Overview of AI and communication for 6G network: Fundamentals, challenges, and future research opportunities. Science China Information Sciences. 2025 Jul;68(7):171301.
12. Pennanen H, Hänninen T, Tervo O, Tölli A, Latva-Aho M. 6G: The intelligent network of everything. IEEE Access. 2024 Dec 23;13:1319-421.
13. Tao Z, Xu W, Huang Y, Wang X, You X. Wireless network digital twin for 6G: Generative AI as a key enabler. IEEE Wireless Communications. 2024 Aug 7;31(4):24-31.
14. Chen M, Hao Y, Hwang K, Wang L, Wang L. Disease prediction by machine learning over big data from healthcare communities. IEEE access. 2017 Apr 26;5:8869-79.
15. Cui Q, You X, Wei N, Nan G, Zhang X, Zhang J, Lyu X, Ai M, Tao X, Feng Z, Zhang P. Overview of AI and communication for 6G network: Fundamentals, challenges, and future research opportunities. Science China Information Sciences. 2025 Jul;68(7):171301.

Wireless communication has moved through five complete technology generations in roughly four decades, and each transition has reshaped how societies exchange information, run businesses, and design cities. This paper is the first instalment of a two-part review and concentrates on the historical arc of that journey, tracing the defining traits, benefits, and shortcomings of 1G through 5G before turning to the architectural groundwork on which sixth-generation (6G) networks are being built. Particular attention is paid to how sixth-generation systems are expected to fold artificial intelligence (AI) directly into the network fabric through a Digital Twin (DT) framework, rather than bolting it on as an external add-on. We also examine the energy-optimisation strategies that will decide whether 6G's ambitious performance targets can be met without a runaway rise in power consumption. To make the generational transition easier to visualise, we include a comparative summary table together with two illustrative charts depicting the approximate growth in peak data rate and the corresponding fall in latency across generations. The discussion closes by outlining the DT communication mechanism and the twin-loop management structure that is likely to underpin autonomous 6G operation, setting the stage for the companion paper, which examines specific AI techniques and air-interface optimisation methods in detail.

Keywords - 6G networks, mobile generations, wireless evolution, Digital Twin, network architecture, energy efficiency, artificial intelligence.

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Chowdhury MZ, Shahjalal M, Ahmed S, Jang YM. 6G wireless communication systems: Applications, requirements, technologies, challenges, and research directions. IEEE Open Journal of the Communications Society. 2020 Jul 20;1:957-75.
2. Saad W, Bennis M, Chen M. A vision of 6G wireless systems: Applications, trends, technologies, and open research problems. IEEE network. 2019 Oct 15;34(3):134-42.
3. Tataria H, Shafi M, Molisch AF, Dohler M, Sjöland H, Tufvesson F. 6G wireless systems: Vision, requirements, challenges, insights, and opportunities. Proceedings of the IEEE. 2021 Mar 30;109(7):1166-99.
4. Recommendation IT. Framework and overall objectives of the future development of IMT for 2030 and beyond. International Telecommunication Union (ITU) Recommendation (ITU- R). 2023 Jun.
5. Yuan Y, Zhao Y, Zong B, Parolari S. Potential key technologies for 6G mobile communications. Science China Information Sciences. 2020 Aug;63(8):183301.
6. Tao F, Zhang M. Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing. IEEE access. 2017 Sep 25;5:20418-27.
7. Tao F, Qi Q, Wang L, Nee AY. Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparison. Engineering. 2019 Aug 1;5(4):653-61.
8. Tao F, Zhang H, Liu A, Nee AY. Digital twin in industry: State-of-the-art. IEEE Transactions on industrial informatics. 2018 Oct 1;15(4):2405-15.
9. Rappaport TS, Xing Y, Kanhere O, Ju S, Madanayake A, Mandal S, Alkhateeb A, Trichopoulos GC. Wireless communications and applications above 100 GHz: Opportunities and challenges for 6G and beyond. IEEE access. 2019 Jun 6;7:78729-57.
10. Ma L, Grant M, Lin H, Sköld J, Liu R, Shao J. From Vision to Design Targets: Technical Performance Requirements for IMT-2030. IEEE Communications Magazine. 2026 Jun 3;64(6):6-9.
11. Cui Q, You X, Wei N, Nan G, Zhang X, Zhang J, Lyu X, Ai M, Tao X, Feng Z, Zhang P. Overview of AI and communication for 6G network: Fundamentals, challenges, and future research opportunities. Science China Information Sciences. 2025 Jul;68(7):171301.
12. Pennanen H, Hänninen T, Tervo O, Tölli A, Latva-Aho M. 6G: The intelligent network of everything. IEEE Access. 2024 Dec 23;13:1319-421.
13. Tao Z, Xu W, Huang Y, Wang X, You X. Wireless network digital twin for 6G: Generative AI as a key enabler. IEEE Wireless Communications. 2024 Aug 7;31(4):24-31.
14. Chen M, Hao Y, Hwang K, Wang L, Wang L. Disease prediction by machine learning over big data from healthcare communities. IEEE access. 2017 Apr 26;5:8869-79.
15. Cui Q, You X, Wei N, Nan G, Zhang X, Zhang J, Lyu X, Ai M, Tao X, Feng Z, Zhang P. Overview of AI and communication for 6G network: Fundamentals, challenges, and future research opportunities. Science China Information Sciences. 2025 Jul;68(7):171301.